Bounded Size Graph Clustering with Applications to Stream Processing

We introduce a graph clustering problem motivated by a stream processing application. Input to our problem is an undirected graph with vertex and edge weights. A cluster is a subset of the vertices. The size of a cluster is defined as the total vertex weight in the subset plus the total edge weight at the boundary of the cluster. The bounded size graph clustering problem (BSGC) is to partition the vertices into clusters of size at most a given budget and minimize the total edge-weight across the clusters. In the multiway cut version of the problem, we are also given a subset of vertices called terminals. No cluster is allowed to contain more than one terminal. Our problem differs from most of the previously studied clustering problems in that the number of clusters is not specified. We first show that the feasibility version of the multiway cut BSGC problem, i.e., determining if there exists a clustering with bounded-size clusters satisfying the multiway cut constraint, can be solve...

• Type: Conference
• Year: 2009
• Where: FSTTCS
• Authors: Rohit Khandekar, Kirsten Hildrum, Sujay Parekh, Deepak Rajan, Jay Sethuraman, Joel L. Wolf
• Keywords: Clustering Problems, FSTTCS 2009, Graph Clustering Problem, Multiway Cut